Instructions to use hf-internal-testing/tiny-random-UdopModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UdopModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-UdopModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-UdopModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-UdopModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6dd022bcb3fc8768418470931bd8bfb32abf95daa062e1a3b37fe5856880910
- Size of remote file:
- 4.83 MB
- SHA256:
- e3940c357b57a870f78ffd2ea4f2b27bbc43dbab4751df760a572e1c0576cf41
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.